code: def __init__(self, params):
      super(DecisionTreeAlgorithm, self).__init__(params)
      logger.debug("DecisionTreeAlgorithm.__init__")
      self.library_version = sklearn.__version__
      self.max_iters = additional.get("max_steps", 1)
      self.model = DecisionTreeClassifier(
          criterion=params.get("criterion", "gini"),
          max_depth=params.get("max_depth", 3),
          random_state=params.get("seed", 1),
      )
  
imports: import logging
  import os
  import warnings
  import numpy
  import sklearn
  from sklearn.base import BaseEstimator, ClassifierMixin, RegressorMixin
  from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
  from supervised.algorithms.algorithm import BaseAlgorithm
  from supervised.algorithms.registry import BINARY_CLASSIFICATION, MULTICLASS_CLASSIFICATION, REGRESSION, AlgorithmsRegistry
  from supervised.algorithms.sklearn import SklearnAlgorithm
  from supervised.utils.config import LOG_LEVEL
  import dtreeviz
  from sklearn.tree import _tree
  from supervised.utils.subsample import subsample
label_desc: Use image node_id 1 to create a new DecisionTreeAlgorithm object from inherited base classes: SklearnAlgorithm, BaseEstimator, ClassifierMixin with example: obj = DecisionTreeAlgorithm(params)